Flipboard

NOVEMBER 15, 2024

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment. Each table represents a single data store.

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AWS Machine Learning Blog

APRIL 16, 2024

They’re often used with highly sensitive business data, like personal data, compliance data, operational data, and financial information, to optimize the model’s output. At AWS, our top priority is safeguarding the security and confidentiality of our customers’ workloads.

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AWS Machine Learning Blog

JULY 8, 2024

Eviden is an AWS Premier partner , bringing together 47,000 world-class talents and expanding the possibilities of data and technology across the digital continuum, now and for generations to come. We complement individual learning with hands-on opportunities, including Immersion Days , Gamedays , and using AWS DeepRacer.

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Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. These skilled professionals are tasked with building and deploying models that improve the quality and efficiency of BMW’s business processes and enable informed leadership decisions.

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AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

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AWS Machine Learning Blog

JULY 8, 2024

As industries begin adopting processes dependent on machine learning (ML) technologies, it is critical to establish machine learning operations (MLOps) that scale to support growth and utilization of this technology. There were noticeable challenges when running ML workflows in the cloud.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment. For more information on how to view and increase your quotas, refer to Amazon EC2 service quotas.

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AWS Machine Learning Blog

MAY 30, 2024

Organizations across media and entertainment, advertising, social media, education, and other sectors require efficient solutions to extract information from videos and apply flexible evaluations based on their policies. This solution, powered by AWS AI and generative AI services, meets these needs.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. Some applications may need to access data with personal identifiable information (PII) while others may rely on noncritical data.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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AWS Machine Learning Blog

SEPTEMBER 4, 2024

Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. Amazon SageMaker provides capabilities to remove the undifferentiated heavy lifting of building and deploying ML models. This entire workflow is shown in the following solution diagram.

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AWS Machine Learning Blog

JANUARY 24, 2024

Despite their wealth of general knowledge, state-of-the-art LLMs only have access to the information they were trained on. This can lead to factual inaccuracies (hallucinations) when the LLM is prompted to generate text based on information they didn’t see during their training.

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AWS Machine Learning Blog

FEBRUARY 26, 2024

By using AWS services, our architecture provides real-time visibility into LLM behavior and enables teams to quickly identify and address any issues or anomalies. In this post, we demonstrate a few metrics for online LLM monitoring and their respective architecture for scale using AWS services such as Amazon CloudWatch and AWS Lambda.

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AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

Legal tech professionals, like any other business handling sensitive customer information, require robust security and confidentiality practices. AWS AI and machine learning (ML) services help address these concerns within the industry. AWS AI and machine learning (ML) services help address these concerns within the industry.

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AWS Machine Learning Blog

JUNE 26, 2024

Artificial intelligence and machine learning (AI/ML) technologies can assist capital market organizations overcome these challenges. Intelligent document processing (IDP) applies AI/ML techniques to automate data extraction from documents. These applications come with the drawback of being inflexible and high-maintenance.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

AWS can play a key role in enabling fast implementation of these decentralized clinical trials. By exploring these AWS powered alternatives, we aim to demonstrate how organizations can drive progress towards more environmentally friendly clinical research practices.

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AWS Machine Learning Blog

JULY 3, 2024

To solve this problem, this post shows you how to apply AWS services such as Amazon Bedrock , AWS Step Functions , and Amazon Simple Email Service (Amazon SES) to build a fully-automated multilingual calendar artificial intelligence (AI) assistant. It lets you orchestrate multiple steps in the pipeline.

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AWS Machine Learning Blog

JULY 31, 2024

Amazon Web Services (AWS) is committed to supporting the development of cutting-edge generative artificial intelligence (AI) technologies by companies and organizations across the globe. Let’s dive in and explore how these organizations are transforming what’s possible with generative AI on AWS.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

This wealth of content provides an opportunity to streamline access to information in a compliant and responsible way. Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles.

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AWS Machine Learning Blog

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders).

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AWS Machine Learning Blog

AUGUST 5, 2024

RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer based on the retrieved information. Prerequisites To implement the solution provided in this post, you should have the following: An active AWS account and familiarity with FMs, Amazon Bedrock, and OpenSearch Serverless.

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AWS Machine Learning Blog

MARCH 13, 2024

In this post, we introduce solutions that enable audio and text chat moderation using various AWS services, including Amazon Transcribe , Amazon Comprehend , Amazon Bedrock , and Amazon OpenSearch Service. Amazon Transcribe converts the audio into text, providing additional information about toxicity analysis.

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AWS Machine Learning Blog

JULY 17, 2024

As a customer, you rely on Amazon Web Services (AWS) expertise to be available and understand your specific environment and operations. This allows you to easily identify and reference the underlying information sources that informed the AI’s response, providing more context and enabling further exploration of the topic if needed.

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AWS Machine Learning Blog

APRIL 29, 2024

Close collaboration with AWS Trainium has also played a major role in making the Arcee platform extremely performant, not only accelerating model training but also reducing overall costs and enforcing compliance and data integrity in the secure AWS environment. Our cluster consisted of 16 nodes, each equipped with a trn1n.32xlarge

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AWS Machine Learning Blog

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Scaling machine learning (ML) workflows from initial prototypes to large-scale production deployment can be daunting task, but the integration of Amazon SageMaker Studio and Amazon SageMaker HyperPod offers a streamlined solution to this challenge. Make sure you have the latest version of the AWS Command Line Interface (AWS CLI).

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AWS Machine Learning Blog

NOVEMBER 26, 2024

Amazon SageMaker Studio is the first integrated development environment (IDE) purposefully designed to accelerate end-to-end machine learning (ML) development. These automations can greatly decrease overhead related to ML project setup, facilitate technical consistency, and save costs related to running idle instances.

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Flipboard

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. We provide detailed information and GitHub examples for this new SageMaker capability. We discuss this in Part 2.

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AWS Machine Learning Blog

MAY 7, 2024

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. SageMaker JumpStart is a machine learning (ML) hub with foundation models (FMs), built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks.

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AWS Machine Learning Blog

MAY 8, 2024

In 2022, Dialog Axiata made significant progress in their digital transformation efforts, with AWS playing a key role in this journey. Dialog Axiata runs some of their business-critical telecom workloads on AWS, including Charging Gateway, Payment Gateway, Campaign Management System, SuperApp, and various analytics tasks.

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

This capability opens up innovative avenues for image understanding, wherein Anthropic’s Claude 3 models can analyze visual information in conjunction with textual data, facilitating more comprehensive and contextual interpretations. AWS Fargate is the compute engine for web application.

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Flipboard

NOVEMBER 19, 2024

Amazon Bedrock offers a serverless experience so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage infrastructure. This can lead to inefficiencies, delays, and errors, diminishing customer satisfaction.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. The AWS Command Line Interface (AWS CLI) installed on your machine to upload the dataset to Amazon S3. For more information on managing credentials securely, see the AWS Boto3 documentation.

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AWS Machine Learning Blog

MAY 30, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. AWS Prototyping developed an AWS Cloud Development Kit (AWS CDK) stack for deployment following AWS best practices.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. For more information about this architecture, see New – Code Editor, based on Code-OSS VS Code Open Source now available in Amazon SageMaker Studio.

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Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

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